Video and image content often contains numerous objects that are visible to a viewer. Although a human viewer may perceive the objects shown in the video or image content with little effort, it is no easy task for a machine or computer to recognize and identify the objects. Moreover, objects in a video, that is, an image stream, may constantly change, move, appear, disappear, etc. As such, computerized object recognition in a continuous video/image stream often requires a tremendous amount of computation power. This task is a challenge for many user devices (e.g., smart TVs, personal computers, smart phones) that have limited computing resources.
Moreover, it is often desirable to know and use information related to the objects shown in the video or image content. For example, although a human viewer can easily determine that an object currently shown on a TV screen is a car, the viewer still does not know the maker, year, price of the car, or which dealer around the neighborhood currently carries in its inventory the car in the depicted color. As another example, video content may include the clothing that certain people are wearing, electronics that they are using, and cars that they are driving. A viewer may be inclined to purchase such objects (i.e., products) or at least learn more information about them. The viewer may, however, be unable to identify the products or know where to purchase such products. The viewer may also not know price information about the products.
Current content delivery systems, such as Netflix, Apple TV, and Amazon Prime provide streaming video content, but do not include any recognition or identification of products that are present in the video content. Thus, as discussed above, while a viewer may desire to purchase or learn more about a product shown in the video content, current content delivery systems do not offer a means for the viewer to learn any information about the product. Moreover, brands and merchants cannot use the current content delivery systems to make potential sales to such a viewer.
Similar issues may exist in regard to digital images that are present in digital photo galleries, which may be located on social media websites or other internet web pages. While these images may include numerous products that the viewer is interested in purchasing or learning about, a viewer may not know how or where to purchase the item, and may not know any other information about the product, such as its brand, or how much it costs.
In view of the shortcomings of current systems, systems and methods for automated object recognition are desired.